Experimental Evidence That AI-Managed Workers Tolerate Lower Pay Without Demotivation

TL;DR

This study provides experimental evidence that workers managed by AI accept lower wages without feeling demotivated, due to muted emotional responses and perceived impartiality of AI management.

Contribution

It introduces a high-fidelity experimental platform in Minecraft to systematically compare worker responses to AI, human, and hybrid management, revealing AI's potential for silent exploitation.

Findings

AI management leads to 40% lower wages without reducing motivation.

Workers exhibit muted emotional reactions to AI evaluation.

AI's impartial appearance may enable silent exploitation.

Abstract

Experimental evidence on worker responses to AI management remains mixed, partly due to limitations in experimental fidelity. We address these limitations with a customized workplace in the Minecraft platform, enabling high-resolution behavioral tracking of autonomous task execution, and ensuring that participants approach the task with well-formed expectations about their own competence. Workers (N = 382) completed repeated production tasks under either human, AI, or hybrid management. An AI manager trained on human-defined evaluation principles systematically assigned lower performance ratings and reduced wages by 40\%, without adverse effects on worker motivation and sense of fairness. These effects were driven by a muted emotional response to AI evaluation, compared to evaluation by a human. The very features that make AI appear impartial may also facilitate silent exploitation, by suppressing the social reactions that normally constrain extractive practices in human-managed work.